Internet of Things bloghttps://www.ibm.com/blogs/internet-of-things
The IBM IoT (Internet of Things) blog. The very latest IoT news, and blogs from IBM. Internet of Things info on security, connected buildings, automotive, Watson IoT, and cognitive computing.Wed, 21 Feb 2018 14:29:49 +0000en-UShourly1https://wordpress.org/?v=4.7.9How the gig economy will transform field service managementhttps://www.ibm.com/blogs/internet-of-things/iot-fsm-and-gig-economy/
https://www.ibm.com/blogs/internet-of-things/iot-fsm-and-gig-economy/#respondTue, 20 Feb 2018 22:24:48 +0000https://www.ibm.com/blogs/internet-of-things/?p=63882A use case for the future Imagine the scenario: a master electrician is responsible for fixing motors, transformers, generators and electronic controllers on industrial robots. He finishes the first shift at a manufacturing plant, gets an alert on his phone as he’s driving home. Something is wrong with a nearby photovoltaic system – aka a […]

Imagine the scenario: a master electrician is responsible for fixing motors, transformers, generators and electronic controllers on industrial robots. He finishes the first shift at a manufacturing plant, gets an alert on his phone as he’s driving home. Something is wrong with a nearby photovoltaic system – aka a solar array – operated by a regional energy provider. The company is offering $125 an hour to someone who can fix the problem in the next four hours. It’s easy money – so he accepts the job and his phone guides him to a field a few miles away.

He arrives on site, grabs his tools, and puts on his augmented reality glasses. On his phone he receives the work order from the energy company for the troublesome equipment. An hour before, the company had received an alert that the electrical output from the system is atypical based on the current weather conditions. He reviews the system blueprints on his phone. Following a blueprint map displayed on his glasses, he begins his inspection.

After some testing, he realizes there is a problem with the inverter and calls the energy company’s engineering team. They help him diagnose the problem based on a video stream from his glasses to their headquarters 200 miles away. After some wiring improvements guided by the engineers, the system is performing well. And he receives a $125 payment directly in his bank account within 5 minutes of leaving the job site.

The rise of the gig economy

Currently, stories such as the one above are uncommon. But, with extreme growth and interest predicted in freelancing, this may not always be the case. The application of gig economy staffing models to industry seems inevitable.

So, what does this mean? Well, the gig economy refers to the increase in the number of temporary, flexible jobs. It also incorporates the trend of companies hiring independent contractors and freelancers instead of full-time employees. It’s widely believed that over 30 percent of the U.S. workforce is involved in the gig economy.

A freelance economy specifically refers to hiring self-employed workers to undertake specific, short-term jobs in return for an agreed upon wage. There are lots of examples of B2C companies using the gig economy to support their business models – such as Uber, Lyft, TaskRabbit, Instacart, Airbnb and Shyp.

Field Service Management basics

Field service management (FSM) is the process of planning and dispatching workers to a location to meet service commitments. It’s complex. Companies need to predict service needs, forecast staffing around demand, schedule work efficiently, and enable staff to complete works.

Technology is already changing how the FSM process works at its core. For example, using weather data and advanced analytics from equipment data in the field, companies can more accurately predict outages and deploy their workforce. Systems such as Maximo are used to track work orders and maintenance records for all field infrastructure. Maximo Anywhere enables field technicians to work more productively on site. It’s no wonder the world’s largest asset-intensive organizations rely on IBM for operations solutions.

How will technology enable freelancing in FSM?

There are a few emerging technologies that will make the story above become real, faster than anyone is anticipating. First, the Internet of Things is connecting equipment and operations in unimaginable ways. This means improvements in uptime and operational efficiency. With new sources of data, Field Service can be optimized much more efficiently.

Second, artificial intelligence (AI) is changing how field equipment is managed. For example, IBM provides the ability to apply analytics to video and audio to see whether there are issues in the field. AI can also help optimize the deployment of field resources. This is partly because machine learning models can account for more variables than a human can comprehend.

Over time, services like Watson might be able to give field technicians advice. For instance, by working out the probability that certain equipment is the cause of operational failures. With the world’s computing power at its disposal, Watson might even serve as am educator for apprentice electricians on the job site.

Finally, augmented reality is developing rapidly beyond its initial commercial applications. Not only is augmented reality hardware improving, but the software powering the hardware is finding powerful industrial use cases. In the near future, cloud-based solutions such as Maximo will be easily accessible via augmented reality. This means technicians can both learn from and use Maximo as another tool in their toolbox.

Learn more and join us at Think 2018

When do you think the story above will become a reality? How do you see technology changing field service? We’ll be exploring answers to these questions and more at Think 2018: our landmark conference in Las Vegas. Join us there from 19-22 March, and meet partners, thinkers and innovators from around the world.

In the meantime, you can learn more about Maximo, the world’s leading enterprise asset management solution, by visiting our website.

]]>https://www.ibm.com/blogs/internet-of-things/iot-fsm-and-gig-economy/feed/0How to reduce anxiety over lease accounting changeshttps://www.ibm.com/blogs/internet-of-things/iot-tririga-lease-accounting-changes/
https://www.ibm.com/blogs/internet-of-things/iot-tririga-lease-accounting-changes/#respondTue, 20 Feb 2018 16:18:29 +0000https://www.ibm.com/blogs/internet-of-things/?p=63855If you’re reading this, you probably already know that upcoming changes to regulations issued by the Financial Accounting Standards Board (FASB) and International Accounting Standards Board (IASB) mean that leases are getting capitalized on your books. But do you know the requirements to comply with these new regulations? Or which milestones to hit between now […]

]]>If you’re reading this, you probably already know that upcoming changes to regulations issued by the Financial Accounting Standards Board (FASB) and International Accounting Standards Board (IASB) mean that leases are getting capitalized on your books. But do you know the requirements to comply with these new regulations? Or which milestones to hit between now and when the new standards go into effect this year.

IBM has been preparing for the changes since they were first announced. The company has already incorporated them into the IBM TRIRIGA® integrated workplace management system (IWMS). With TRIRIGA, you’ll be able to navigate through the FASB and IASB changes and ensure compliance with all new regulations.

Identify affected leases and renewal options

The bad news first: If you haven’t already started preparing for these changes, you’re probably behind. Compliance begins in a company’s first fiscal year under the new standard. However, private companies have one additional year before compliance begins. The biggest challenge for many organizations will be collecting all relevant data from their portfolios and identifying all leases. That’s something that’s far easier to do with the aid of TRIRIGA, especially for users of TRIRIGA’s Real Estate Manager software.

Renewal options are a common gap in older lease administration systems. If your company policies will include such options in likely term decisions, you’ll have to go back through your records and track down all renewal information for each individual lease. This underlines the importance of having consistent company-wide policies. With them, it’s easier to structure and expedite implementations across the board.

Under existing lease accounting standards, the accounting for renewal periods begins at the commencement of those periods. Under the new standards, however, there is a requirement to re-measure the new liability at the time the option becomes reasonably certain of being exercised. This requirement is already affecting the lease renewal process, according to lease accounting expert Tracy Owens of eCIFM, an IBM partner and TRIRIGA implementer.

Concerns and solutions: liability

The development of TRIRIGA is done with business operations in mind, starting at the beginning of the lease procurement process. In comparison, other contract management systems are not being built to manage that process. Neither are they built to provide auditability of every lease. TRIRIGA is also easily configured for elements specific to your business.

Still, different members of your organization will have different concerns about the changes. The concern for corporate real estate managers is the liability corporations assume when they sign a lease. Because your real estate team puts assets and liabilities on the balance sheets under the new standards, there is more scrutiny of both. Lease structures built in 1976 under FASB 13 (and in 1984 under IAS 17) will now yield different—and likely worse—results under the new rules. Companies that tackle this new compliance challenge early will be better able to strategically drive ROI on that compliance.

To address concerns about liabilities, TRIRIGA provides a full view of lease terms. This gives corporate managers a clear view into where liabilities can be cut, resulting in savings and increases in efficiency. In most leases, the liability will be larger under the new standards. As companies start to review and restructure their lease timing, TRIRIGA can help. With it, companies can see the impact and measure all the pieces—which is the key to getting results.

Concerns and solutions: the effect on shareholder equity

Corporate finance executives have a specific concern about the lease accounting standard changes: the effect on shareholder equity. When leases go on the books, it reduces this equity. This is where efficient operations and space management will pay off:

Getting the most profitable use out of every space in a real estate portfolio

Eliminating unused space to offset equity loss

Possible additional efficiencies when leases update or come up for renewal.

As Dave Dilworth wrote in June 2017, specific TRIRIGA developments for CFOs and CAOs include sub-ledgers for journaling, closing periods and creating reports. To account for all services and spending, managers and occupants of specific facilities receive mobile app updates.

And if you would like to know more about how TRIRIGA helps make better space management decisions, take a look at this video:

Accounting firms and TRIRIGA

IBM has worked with all of the big four accounting firms in TRIRIGA development and implementation. Two of the four use TRIRIGA for their worldwide portfolios. Many large organizations use the services that these firms provide. They have a keen interest in the accurate and effective incorporation of the lease accounting changes in the software.

Your accounting team, plus other departments in your company, will have plenty to do in preparation for the updates. Staff workloads may increase due to the necessary data entry and data crunching required to implement the new regulations. Your lease administration group may also see an uptick in personnel. The sooner you begin to implement the changes, the easier it will be to manage these workload challenges.

We could do this with spreadsheets, right?

Some lease administrators still juggle spreadsheets or use standard lease administration systems. But those methods quickly become unworkable for companies with real estate portfolios numbering in even the low hundreds. It’s a recipe for introducing errors. Or for leaving gaps in the data while calculating net present value and deciding your likely lease options.

Although your straightforward calculations for, say, a fifteen-year lease will allow for the same payment amount over time, the new standards mean your asset and liability values can change daily. Tracking those daily changes across a multi-lease portfolio is unmanageable and, for all practical purposes, impossible. Oh, and you’ll also have to account for interest changes. To accurately accommodate the FASB and IASB changes, using spreadsheets will not be a viable option.

Sleep easy with TRIRIGA

If you’re not currently a TRIRIGA user, be aware that implementation of the system is not an overnight process. Moreover, the expertise required for accurate implementation is in increasingly short supply as the deadline approaches. Fortunately, eCIFM has a Data Migrator to simplify the move and help you be up and running on TRIRIGA as swiftly as possible. You’ll be able to start using your data to increase efficiency, cut costs and find new revenue opportunities. As the FASB and IASB compliance deadline arrives, you’ll be able to rest easy.

]]>https://www.ibm.com/blogs/internet-of-things/iot-tririga-lease-accounting-changes/feed/0What we THINK about: Enterprise Asset Managementhttps://www.ibm.com/blogs/internet-of-things/iot-think-enterpise-asset-management/
https://www.ibm.com/blogs/internet-of-things/iot-think-enterpise-asset-management/#respondThu, 15 Feb 2018 20:54:03 +0000https://www.ibm.com/blogs/internet-of-things/?p=63813It’s that time of year again. What time, you may be asking? The time of year to think about what new challenges you will take on and how you will execute them. To think about ways your business can innovate with new enterprise asset management (EAM) technologies. And, most importantly, to think of ways to […]

]]>It’s that time of year again. What time, you may be asking? The time of year to think about what new challenges you will take on and how you will execute them. To think about ways your business can innovate with new enterprise asset management (EAM) technologies. And, most importantly, to think of ways to meet and network with new peers and leaders in your industry. Luckily, all of this can be done at IBM Think. In a first-if-its-kind event, IBM is combining all prior events that you may be familiar with (i.e. InterConnect, WoW, Edge, etc) into one incredible event in Vegas from March 19-22. Will you join us?

Network with enterprise leaders

First of many reasons to attend is the people. With 40,000 expected attendees, there will be no shortage of conversations, connections, and education. This will include Ginni Rometty, and the new IoT General Manager, Kareem Yusuf. This is in addition to the many session speakers delivering great content around EAM and the future of IBM Maximo.

Dive deep into innovative Enterprise Asset Management

As track chair for Maximo Enterprise Asset Management, I’ve had the pleasure of helping to bring together some of the most thought-provoking customer stories, and highlight new IBM offerings throughout the track. We’ll be exploring innovative approaches to managing assets and ensuring reliability and uptime. Below, I’ll share just a few of the topics our clients will spotlight during the event.

Keynote: State of the Enterprise Asset Management Union

Our track keynote features Terrance O’Hanlon from ReliabilityWeb, who you may know from their MaximoWorld and IMC annual events. This executive keynote will bring a perspective of steps that can accelerate your journey towards digital transformation. We’ll explore how leaders are using IoT data, predictive maintenance and augmented reality to drive improved EAM outcomes.

Panel session: The next frontier is mobility

A panel session, ‘The next frontier for Enterprise Asset Management is Mobility,’ will focus on Field Service Management. We’ll hear from industry leader Westar Energy and ‘Toughbook’ innovator and partner, Samsung. This session will share best practices on maintaining and servicing assets in the field. By increasing productivity, reducing errors, and capturing data at the work source, mobile can help identify problems before they happen.

GIS and Weather, together

Did you know that IBM Watson uses location and weather data together to drive more effective infrastructure and correction? Especially when it comes to maintaining high-cost and high-risk assets such as wind turbines at sea and transmission towers in rugged terrain.

This session will discuss a new, innovative and integrated deep-learning solution to aid inspection, maintenance and repair of weather-impacted assets. The solution is comprised of:

Watson Visual Recognition

Esri ArcGIS geospatial analytics and map visualization

IBM Maximo Enterprise Asset Management

Weather Company data

Elements of the IBM Data Science Experience (DSX)

When we bring these elements together, we can realize two immediate benefits: improved worker safety and lower maintenance costs.

Managing your robotic assets

How does the world’s largest industrial robot maker manage a cognitive factory? Masahiro Ogawa, Corporate VP & GM Robotics Division, Yaskawa Electric, will be at THINK to tell us.

How EAM is reinventing operations

IBM’s Stephan Biller, VP of IoT Product Strategy talks us through the way companies are reinventing operations with Enterprise Asset Management. Stephan will examine how to get the most value from enterprise assets connected to a digital ecosystem. He’ll also explore how data analysis can yield insights that drive smart-decision making for predictive maintenance and inventory optimization.

At this session you can learn from organizations that are well on their way to achieving this. Organizations that are using digital twin to improve processes and asset reliability. And performing cutting-edge analytics on asset and business process data to uncover patterns and optimize inventory. You will walk away with more than just new ideas. You’ll also have the practical information necessary to help you drive excellence in your company’s business operations.

This session provides an overview of IBM Maximo and Blockchain integration. It will cover available solutions, use cases and how to get started. Connecting Blockchain applications to Maximo streamlines business processes and opens up new business opportunities. Maximo can send transactional data to the blockchain, which incorporates the data into a business transaction. It then stores the record in a shared, indelible ledger. Secure and irrefutable sharing of data between parties enables a new generation of open, transactional applications that streamline business processes.

Talk to our clients and partners

Our clients and partners are ready to share their Enterprise Asset Management experiences. You’ll learn how Esri, Daqri and Samsung are expanding the ability of Enterprise Asset Management to ‘locate’ and ‘see’ assets in the field. You’ll hear from our energy and utilities clients: Cenovus Energy, Kuwait Oil Company, Diamond Offshore and Yaskawa Electric. Or our transportation clients, Atlanta’s MARTA, Cummins, and Amsterdam’s Schiphol Airport. The campus floor will bring additional opportunities to learn. I really appreciate the thoughtfulness that’s been put into really making it feel more like a community – with theatre sessions, demos and food service all contained in our Business and AI area. There will be a cognitive car and cognitive factory exhibits and lots of time for networking and interaction.

Not convinced yet? Let us entertain you!

These are just some of the highlights, but there’s a lot more to come. You can even build a tailored curriculum with the help of IBM Watson to ensure you use your time effectively. Get started here.

And finally, there’s the all-important chance to let your hair down. The growing entertainment line-up includes award-winning performers Train, Bare Naked Ladies (BNL) and the Chainsmokers. How are you going to decide?

Register today

I hope that helps convince you of the value that Think will provide. I look forward to seeing you there! Register today for THINK 2018, and join me and 39,999 friends in Las Vegas.

]]>https://www.ibm.com/blogs/internet-of-things/iot-think-enterpise-asset-management/feed/0What we THINK about: Manufacturinghttps://www.ibm.com/blogs/internet-of-things/iot-what-we-think-about-manufacturing/
https://www.ibm.com/blogs/internet-of-things/iot-what-we-think-about-manufacturing/#respondThu, 15 Feb 2018 18:16:51 +0000https://www.ibm.com/blogs/internet-of-things/?p=63783It’s time to THINK about: Manufacturing. What are the technologies and capabilities that will affect the manufacturing industry in 2018? How can we leverage key innovations like artificial intelligence (AI) and cognitive computing to drive efficiencies? How can we reinvent and innovate to create better experiences for our customers? If these questions are on your […]

]]>It’s time to THINK about: Manufacturing. What are the technologies and capabilities that will affect the manufacturing industry in 2018? How can we leverage key innovations like artificial intelligence (AI) and cognitive computing to drive efficiencies? How can we reinvent and innovate to create better experiences for our customers? If these questions are on your mind, you’ll find answers at IBM Think 2018. It’s a unique new event that brings together 40,000 thinkers, educators and innovators in one place. Best of all, it’s in Las Vegas! Here are some of the reasons we think you’ll want to be there.

Hear first-hand how many of the world’s most visionary brands are deploying IoT

Joining us throughout the event will be many of our most important clients. These clients will inspire you by sharing their stories about how they are bringing IoT and AI solutions together to respond to business challenges in manufacturing. We look forward to these real-life stories helping you to reimagine your businesses with the promise of IoT and AI.

Hear our vision for the future

We believe in outcomes. In beginning with the end in mind. In strategic decision-making to support well-defined goals. We want to share this vision with you. Across the many large theater, breakout sessions, demos and networking opportunities, you will hear our vision for the future of manufacturing operations. We will help you to understand what’s coming next. By aligning this vision with practical applications, we’ll empower you to begin your IoT journey today.

For example, below are just some of the panel sessions, demos and learning opportunities we think you’ll enjoy. For the personal touch, you can also design your unique agenda with the help of Watson Session Expert.

Engage with our solutions first-hand through show floor activations and demos

The best way to understand the benefits technology can bring your business is to see that technology in action. Join us on the show floor to see many manufacturing use-case demos. We’ll demonstrate how our Visual Insights technology can accurately spot quality defects. How our Acoustic Insights help manufacturers hear potential equipment issues. And how our IoT Equipment Advisor solution uses condition monitoring and past maintenance history to offer prescriptive maintenance and repair guidance. See the technology live and inquire about how it can help address your unique challenges.

Engage with our technical and product leadership

During the event there will be countless opportunities to engage one-to-one with our technical and product leaders. In many cases these people have decades of experience helping manufacturers solve problems. With them, you can hear about our vision, understand our roadmaps, and go deep on product capabilities. Think will be an important opportunity for us to share our views, hear your reaction, and explore together how our rich set of manufacturing solutions can help address your unique challenges.

Discover our AI-powered solutions for manufacturers

IBM has built a robust portfolio of machine learning and AI-powered solutions that address many manufacturing plant operator’s concerns. You’ll find predictive analytics technology that can bring new power to your asset management solutions. We have AI-powered visual and acoustic technology that can spot quality defects. We even can apply our analytics to plant operations to help plant operators maximize throughput and better manage energy consumption. All of our solutions are geared around core drivers of operational efficiency: challenges like asset downtime, quality, and operational optimization.

At Think 2018 you will find a number of sessions on offer to help demonstrate the transforming power of AI for manufacturers. Discover our portfolio summary, and learn how clients like GM, Kone and others are bringing this technology to life through live deployments.

]]>https://www.ibm.com/blogs/internet-of-things/iot-what-we-think-about-manufacturing/feed/0What we THINK about: facilities management & smart buildingshttps://www.ibm.com/blogs/internet-of-things/think-facilities-management/
https://www.ibm.com/blogs/internet-of-things/think-facilities-management/#respondThu, 08 Feb 2018 14:18:20 +0000https://www.ibm.com/blogs/internet-of-things/?p=63666With the new year in full swing, I have been getting many questions about our upcoming event, Think. Questions such as: Will there be a focus on facilities management and smarter buildings? Will there be real use cases around how IoT & AI make buildings smarter? Are there certification opportunities? Will the entertainment be magnificent? […]

]]>With the new year in full swing, I have been getting many questions about our upcoming event, Think. Questions such as: Will there be a focus on facilities management and smarter buildings? Will there be real use cases around how IoT & AI make buildings smarter? Are there certification opportunities? Will the entertainment be magnificent? The answer to all of the above is, of course, yes.

Specifically, I have had several opportunities to speak with clients who are building the business case to head to IBM THINK for a week of networking, learning and sharing. I’ll share with you what I have shared with them.

40,000 new friends await you at Think

We are expecting 40,000 of the world’s most inspiring innovators, leaders, and thinkers in one place. That’s a lot of brilliance under one roof. On top of that, Ginni Rometty and our newest IoT General Manager, Kareem Yusuf, will share their thoughts about the huge changes happening in facilities, factories and other asset-intensive businesses.

A redesigned campus setting to help teach and inspire you

Buildings, asset management and industrial industries will take the center stage in the “Reimagine your Business” Campus. There will be 90+ campus theater sessions, 61 Watson IoT client & tech sessions and the Watson IoT keynote. There will also be 18+ hands-on labs and Watson IoT certifications. So much to learn, so little time.

A robust facilities management track to go deep

As track chair for IoT/ Facilities management, I have had the distinct honor of helping to curate a track that is intended to create deep insights into some innovative approaches to managing facilities. Just a few of the great facilities management topics that our clients will spotlight during the event are:

Smart buildings 101: How to use your buildings data to help you unlock value for your organization.
This session, with the worldwide facilities leader for E&Y, will be a good level-set for existing and prospective facilities management leaders. Most importantly, we will be showcasing some of the newest investments made in Tririga.

Driving operational excellence through smarter buildings: This session expands on the strategy that asset-intensive industries and facilities leaders are employing to create and extract value from their investments.

What CFOs and Financial Managers Don’t Know about Their Property, Plants and Equipment with Tony Bailey from Umpqua Bank will be a great session on how organizations are dealing with the FASB and IASB lease accounting changes, and how they are working to automate and analyze their way to compliance.

Don’t Fear the Dark: Using Dark Data to Make Enlightened Facilities Management Decisions with UMass Amherst and their integration of IoT data as well as GIS and other data elements to “shine a light” on new insights about the way they manage their campus of buildings.

The Future of Work and Its Impact on Workplace Management will showcase how next-generation technology is being put to work in the office today, and is featuring an update from ISS, as they continue to transform 25,000 buildings globally as they continue the journey to bring AI into play in their facilities, and predict and pre-empt technical issues, as well as create more engaging journeys for their occupants.

In Buildings 2050: The Cognitive Building and Digital Twins, we will hear from Dr. Claire Penny on the use cases that are emerging today for digital twin. The groundwork for the buildings of tomorrow is being created today. If you don’t know about digital twin and how it relates to buildings, check out this webcast.

Competing in retail with the “Connected Store” will showcase how the IoT is being used to improve the experiential, as well as operational environment in fast-moving retail environments, and what it might mean to the workplaces of the future as well.

Nobody gets bored in Vegas

I would be remiss if I did not mention the receptions and networking opportunities that run continuously through the event, and an entertainment line-up that continues to grow. There will be three (!) concerts featuring Train, the Bare Naked Ladies (BNL) and the Chainsmokers. Definitely something for everyone. There is more than enough excitement to leave everyone exhausted.

Register now

I hope that helps put some of the huge investment IBM is making for you into perspective. You should now have all the ammo you need to make the case to your leadership to attend Think. I look forward to seeing you in Las Vegas with me and 39,999 friends.

]]>https://www.ibm.com/blogs/internet-of-things/think-facilities-management/feed/0What makes you Think?https://www.ibm.com/blogs/internet-of-things/iot-what-makes-you-think/
https://www.ibm.com/blogs/internet-of-things/iot-what-makes-you-think/#respondWed, 07 Feb 2018 20:31:44 +0000https://www.ibm.com/blogs/internet-of-things/?p=63651That’s always the question, isn’t it? What inspires you? What motivates you? And what will help you rise above? And now there’s an answer for you: Think. Think is a first-of-its-kind event, March 19-22 in Las Vegas. It’s 40,000 people, coming together in a unique campus setting. It’s for those who seek inspiration and education, […]

Think is a first-of-its-kind event, March 19-22 in Las Vegas. It’s 40,000 people, coming together in a unique campus setting. It’s for those who seek inspiration and education,reinvention and innovation. It’s a place toconnect with experts and seek progress. It’s for understanding what’s going on in the world around AI, Cloud, Data, Security and Systems and discovering what’s possible.

And it’s for those who are ready to reimage business in the era of AI.

#1 Think is real

It’s awesomely compelling stories, brought to life by our Watson IoT clients. You’ll hear how other companies have leveraged Watson AI to drive their own digital transformations. And you’ll learn how they’re:

Designing for a software-connected world to develop products that customers can depend on and partners can connect to

Finding and sustaining new differentiation by transforming existing products with “can’t live without” services, designs and features.

Driving operational excellence with insights from every connected thing.

#3 Think is hands-on

#4 Think is enlightening

The sheer brainpower of our speaker list is mind boggling. Want to hear from the co-founder of string field theory? He’s coming. How about astronauts, chief data scientists, heads of industries and CEOs? They’re coming, too. IBMers, like 800+ leaders, 400+ developers and 200+ Distinguished Engineers? All of whom know so much about technology, innovations and ways to build your enterprises? Of course, they’re coming. And they’re all there for you!

#5 Think is fun

It’s a grand networking event, that puts you in touch with experts, educators, innovators and peers. And when the day is over, the fun continues. World-renowned rockers, Bare Naked Ladies (BNL), GRAMMY winners, Train, and musical phenoms, The Chainsmokers, will keep the party going for us all.

]]>Dynamic digital representations, or Digital Twins, are rapidly changing the way industries design, build and operate their products and processes. Gartner predicts, “by 2021, half of large industrial companies will use Digital Twins, resulting in those organizations gaining a 10 percent improvement in effectiveness.”

Powered by the Cloud, IoT, and AI, Digital Twins enrich complex systems like cars, wind turbines and buildings across their entire life cycles. A Digital Twin combines design, production and operational data. It allows assets to be tested before, during and after production, and across a wide range of environments.

A virtual platform for testing of complex IoT systems with live and simulated data.

Forming a knowledge graph for IoT that combines reasoning with machine learning to allow the system to autonomously analyze and understand life cycle data.

Utilizing a virtual testing platform for IoT systems

In order to test complex IoT Systems, our researchers are using a virtual platform. This allows designers and developers of transportation services to investigate large-scale connected car services. They achieve this by merging simulations of large-scale automotive IoT deployments with proof-of-concept capabilities provided from real world vehicles. This platform is helping automotive partners design their services at scale while accelerating time to market.

The platform also allows drivers of actual vehicles to experience a large-scale connected scenario first hand. This combination of simulated and real-world data generates valuable insights. These insights are critical to user-centric development, resulting in reliable systems that are ready for the market. By embedding the data from actual vehicles into the digital environment, we can test the effects of assisted and autonomous driving in large-scale traffic simulations, in real time.

For example …

In collaboration with University College Dublin (UCD), we are using our virtual testing platform to evaluate a number of new mobility concepts. For example, we are testing a new car sharing mobility service that dynamically adapts to user preferences. This then allows a group of users to meet based on changeable traffic conditions and their variable pick-up time arrangements.

We are also investigating using IoT services to maximize air quality intake for pedestrians and cyclists by reducing their exposure to pollution. Imagine an electric bike using IoT devices, such as mobile phones and sensors. These IoT devices detect and automatically assist the cyclists when traveling through areas of high pollution. In those areas, the engine of the e-bike would be automatically triggered into operation. When that happens, it reduces the cyclist’s pedaling effort, resulting in a lower breathing rate and lower pollution intake. The virtual testing platform can also be used to connect to the e-bike and monitor how the cyclist would actually react to this new service, investigating the interactions between the cyclist and the bike.

Another service solution we are evaluating would reduce a pedestrian’s exposure to car exhaust pollution. How? The AI controls of a hybrid car to automatically switch between combustion and electric mode when the vehicle is in close proximity to pedestrians and cyclists.

These examples illustrate how a virtual testing platform can help accelerate the development of new services. At the same time, it also helps the transportation industry respond to the ever-increasing demands for environmental accountability.

Automating Insights with a knowledge graph for IoT

At IBM Research – Ireland, we are developing AI technologies to connect and understand IoT data in new ways. We’re combining machine learning with knowledge graph reasoning to enhance data being extracted from an IoT network. And we’re also adding layers of semantic meaning to create new insights within the network. This technology is the Digital Thread at the core of each Digital Twin. It connects information along the lifecycle stages into a knowledge graph. This graph then enables new informed decisions and automation of processes.

By using a knowledge graph, we are able to organize data and its variables being extracted into groups and establish the relationships between the data sets and their variables. The knowledge graph provides a shared vocabulary of information that can be used to create a model of a domain, the types of data within it, their properties and the relationships between the data–and we are using natural language to do all of this.

As a result, our AI solution understands the meaning and the relationships between the different types of data within a network or system. This gives our research teams new ways to derive innovative insights from an IoT system and present them as new knowledge and information to end users.

Self-diagnosing problems

For example, take an IoT temperature sensor in a building. The temperature sensor has data readings, the type of data that it is recording and its location. Our AI system understands general concepts of physics and how temperature is influenced by heating or cooling, such as environmental factors, heat system controls and so on. This allows our system to form a knowledge graph to understand the temperature settings within the building and the multiple factors that impact the temperature within its operating environment. This allows for the self-diagnosis of problems within the system while enabling it to learn and understand this relationship over time. It is also scalable and works across industries such as retail and automotive.

This combination of simulated and real-world data generates valuable insights that are critical to systems development. Our knowledge graph for IoT is a scalable solution that enables IoT to learn system behaviors, to understand management operations and to self­-diagnose problems. And all while making human­-machine interaction more natural and intuitive.

We will demonstrate the knowledge graph for IoT at the IEEE flagship IoT conference World Forum IoT, February 5-8th in Singapore. A prototype of the virtual testing platform will be shown at the ENABLE-S3 consortium General Assembly, Review and Marketplace event. This is scheduled at our Research lab in Dublin on July 4, 2018.

]]>https://www.ibm.com/blogs/internet-of-things/iot-digital-twins-foster-innovation/feed/0Why quality is the obstacle to mass adoption of 3D printinghttps://www.ibm.com/blogs/internet-of-things/iot-3d-printing-quality-manufacturing/
https://www.ibm.com/blogs/internet-of-things/iot-3d-printing-quality-manufacturing/#respondMon, 05 Feb 2018 15:40:36 +0000https://www.ibm.com/blogs/internet-of-things/?p=63567Additive manufacturing (AM), also known as 3D printing, is a hot topic. Although the technology was invented in the 1980s, only now is it getting industry traction. In fact, in 2017 Gartner’s famous hype cycle predicted that additive manufacturing is moving past disillusionment and into real product applications. Many predict AM will cause massive industry […]

]]>Additive manufacturing (AM), also known as 3D printing, is a hot topic. Although the technology was invented in the 1980s, only now is it getting industry traction. In fact, in 2017 Gartner’s famous hype cycle predicted that additive manufacturing is moving past disillusionment and into real product applications. Many predict AM will cause massive industry disruption. Not only for manufacturers but also for everyone involved in the manufacturing supply chain. This includes transportation and logistics companies, retailers, and many others. In a 2017 study by PwC, 74% of participants agreed that companies investing in 3D printing today will have a significant competitive advantage.

There are many reasons for the rapid growth and interest in 3D printing for manufacturers. For example, the actual printing process is getting faster. CAD software providers are providing feature-rich solutions explicitly for this purpose, and there are viable use cases beyond prototyping or home use. But there is one huge obstacle to adoption in the largest, most productive use cases – quality.

A killer 3D printing use case – spare parts

Take the example of spare parts. Most asset-intensive businesses aggressively manage spare parts inventories. This is not only because they tie up capital but also because a failure to have a spare part available in a crisis can derail operations. 3D printing is viewed by many as a game-changing solution to spare parts problems – just print what you need, just in time. In the same PWC study, only 10% of German industrial firms surveyed use additive manufacturing for spare parts currently. However, 85% expect to do so within 5 years.

Under traditional operating models, quality is inherent in the manufacturing of spare parts. But quality of spare parts produced by 3D printing is anything but certain. For spare part 3D printing to be considered reliable, the quality must be:

Proven and repeatable under stable production processes – similar printers, materials, operators, etc.

Consistent across locations and operations, under any conditions

Guaranteed without input from the part’s designer

This isn’t easy for companies whose core business may have nothing to do with manufacturing. Here are 3 risks when an asset-intensive business shifts from spare part procurement and management to manufacturing parts themselves.

Quality of source materials

Process manufacturers understand that quality in equals quality out. Often relationships with materials providers are closely guarded or even contractually protected. Because many 3D printing equipment and solutions vendors have little to no experience with manufacturing, the burden for sourcing materials for additive manufacturing falls on the business producing spare parts with their printers. Unknown quality source materials present a large potential operational risk. This is especially true if the parts are used in mission-critical equipment or have a role in the production of quality-sensitive products such as medical devices, food products, and many others.

Quality in the manufacturing process

Ensuring that a specific manufacturing process produces quality parts is a science. It is a combination of advanced engineering, materials science, and flawless operational execution. For spare parts manufacturers, providing 3D printing solutions with consistent quality standards may be a disruptive model for supply chains and solve many operational challenges. But for spare part users, manufacturing on their own may be constrained – at least for the near future – to a fraction of their spare parts inventory that isn’t mission critical. In a model where parts manufacturers provide a blueprint for companies to print on their own, ensuring quality in the manufacturing process is essentially impossible. Even if 3D printing is consistently producing parts, ensuring quality requires insights from the OEM/blueprint designer. On its own, this isn’t a scalable model.

Quality control

Every traditional manufacturing process has quality control built into it, that vary from manual inspection to the application of artificial intelligence and machine learning to advanced manufacturing operations. But since 3D printing is a constant, linear process, it tends to lack rigor with quality control (QC). Because the industry is just emerging, there are no clear solutions to QC. One emerging idea is to apply visual inspection to the 3D printing process. This option is fairly cheap if done at scale. It can be done at the printing site– it only relies on software and a high-definition camera. But it does require the parts designer to train the machine learning algorithms.

In the coming years, we will surely see QC solutions come to market designed specifically for additive manufacturing.

Additive manufacturing is shifting from a promising technology to a powerful disruptor, and its gaining momentum with complex ties to many adjacent transformative technology movements such as the ubiquity of the Internet of Things, the industrial use of digital twins, and the public and private investments in Industry 4.0 transformations. IDC forecasts that in 2018, worldwide spending on 3D printing will be nearly $12 Billion. Every manufacturer should think about its additive manufacturing strategy. But at the same time, responsible large-scale adoption must be done with an eye towards quality.

]]>https://www.ibm.com/blogs/internet-of-things/iot-3d-printing-quality-manufacturing/feed/0Connecting hardware and software lifecycles to build the Internet of Thingshttps://www.ibm.com/blogs/internet-of-things/hardware-software-lifecycle/
https://www.ibm.com/blogs/internet-of-things/hardware-software-lifecycle/#respondThu, 01 Feb 2018 16:12:49 +0000https://www.ibm.com/blogs/internet-of-things/?p=43930Traditional software development practices and tools can’t scale up to support the accelerated delivery cycles and iterations of products designed for the Internet of Things. You need modern tools and practices designed for the IoT to succeed. In the past, traditional development methodologies were waterfall and led in one direction: from design to deployment, with […]

]]>Traditional software development practices and tools can’t scale up to support the accelerated delivery cycles and iterations of products designed for the Internet of Things. You need modern tools and practices designed for the IoT to succeed.

In the past, traditional development methodologies were waterfall and led in one direction: from design to deployment, with little data coming back to the development team from deployed products. However, in the Internet of Things, embedded software and sensors in the hardware send operational data back for analysis and action back to the developers. Real-world usage data is now available for developers to improve the quality and usability of their products quickly. We refer to the IoT development process as a feedback loop.

Teams that have successfully leveraged agile methods to improve software delivery now want to carry that over to hardware, to apply the same agile methods to mechanical, electrical design and manufacturing processes. They are challenged with connecting software, hardware and device services components together and linking together the engineering disciplines that deliver these components of the completed product.

Hardware and software configurations evolve at different rates, and keeping track of which software goes with which hardware requires clear connections. As product complexity increases, each component’s configuration and its linkages across the overall product configuration can soon become unmanageable without a system to support the process.

Product lifecycle management

In product lifecycle management (PLM), hardware configurations are managed through the Bill of Materials (BOM). There are several types of BOM including the electrical design, mechanical design and manufactured assembly, such that now a “product” is actually a “system” – and you need a way to trace the parts of that system and their dependencies across the phases of the product development (and deployment) lifecycle with clear linkages. In IoT, this is sometimes referred to as the “digital thread”—the traceability through the nodes of a BOM through its lifecycle and back.

In application lifecycle management (ALM), software configurations are managed through software change and configuration management tools. The capabilities of these tools have become increasingly critical to successful software development as software complexity has increased, software supply chains of different component vendors have evolved, and agile methods have become important to the timely delivery of software.

In the context of IoT development, linking your software configurations with your hardware BOMs is vital to successfully delivering a quality product that can be evolved in the light of changing customer needs informed by operational feedback. Rapid and accurate understanding of the impacts of changes across the whole IoT product, including all aspects of hardware and software, is critical to the IoT lifecycle.

The linking of the worlds of ALM and PLM in this way is a difficult challenge; PLM and ALM tools are typically supplied by different vendors and are often deeply embedded in an organization’s engineering and development processes. ‘Rip and replace’ of existing environments often simply isn’t an option; you need connectivity between the worlds of PLM and ALM.

Linking ALM and PLM is a big step toward digital transformation of product development and realizing the “digital thread”.

]]>https://www.ibm.com/blogs/internet-of-things/hardware-software-lifecycle/feed/0How smart manufacturers bring Industry 4.0 principles to qualityhttps://www.ibm.com/blogs/internet-of-things/iot-industry-4-0-smart-manufacturers/
https://www.ibm.com/blogs/internet-of-things/iot-industry-4-0-smart-manufacturers/#respondTue, 30 Jan 2018 16:35:41 +0000https://www.ibm.com/blogs/internet-of-things/?p=63519Quality matters. Many manufacturers will tell you that poor quality affects both the top and bottom line. They will tell you that the consequences of poor quality are on the rise and that social media can make quality issues devastating to an OEM’s brand. They will also tell you that they are struggling to respond. […]

]]>Quality matters. Many manufacturers will tell you that poor quality affects both the top and bottom line. They will tell you that the consequences of poor quality are on the rise and that social media can make quality issues devastating to an OEM’s brand. They will also tell you that they are struggling to respond. The problem? While the consequences of poor quality are rising, so too are margin pressures. Margin pressures means that budgets are tight and few can respond in traditional ways. Smart manufacturers need to think differently.

Cost of quality is on the rise

Beyond brand impact, poor quality also has a real impact to the bottom line. We must scrap or rework defective products which can eat into overall equipment effectiveness (OEE) measures and lead to plant inefficiency. Challenges only increase once a defective product leaves the factory. Growing supply chain complexity means that products are increasingly costly to find and recall.

Flex – one of the world’s largest electronics makers – estimates that for every $1 spent in product creation, they spend $100 creating resolutions to quality problems.

That is incredible. Solutions may include tracing root cause analysis to identify problems upstream with raw material inputs or downstream with the manufacturing process. It may also mean going back to product development to understand how product design contributes to quality.

Different industries; different impacts on quality

The implication of poor quality changes depending on the industry. For example, volume matters in the electronics industry. OEMs produce dozens of products per minute which means that a defect in a cell phone casing or circuit board assembly can be replicated hundreds of times before they identify and resolve the issue. That is a lot of potential scrap or rework. Smart electronics OEMs look for solutions that impact inspection speed. They need to quickly identify a quality issue, understand the root cause, and implement a resolution before hundreds of defective units are created.

Automotive companies have a different challenge. Here, OEMs are focused on manufacturing precision. Millimeters matter and a high degree of automation means that poorly calibrated equipment can cause small but meaningful variances. Sometimes these variances can be small – so small that only highly trained human inspectors with sophisticated testing tools can spot the difference. Smart automotive OEMs look for solutions that can help human inspectors identify these very small deviations with more accuracy.

Traditional manual inspections can be problematic. Quality inspection is a high-pressure job and the sole reliance on humans without new tools or methods can be slow and ineffective. Humans make mistakes. We get tired and have bad days. We require extensive training to spot defects and retraining to keep pace with new models. All this can hinder agility – a problem which intensified as our labor force ages and retires.

Some OEMs are getting smarter

Increasingly smart OEMs across a range of industries are approaching IBM about ways to get smarter with their quality inspection process. These firms are looking for help bringing technology – specifically machine learning and AI to bear on the problem. Fortunately, IBM has a number of solutions that can help.

Some firms are seeking to better understand the factors that contribute to quality. Have we exceeded quality thresholds? Does temperature or humidity play a role? What about equipment age and maintenance cycles? IBM has a statistical-based solution – called Prescriptive Quality – that dynamically weighs variables that might contribute to issues. This is a great solution when inspectors cannot identify quality based on an image or sound.

One of the hottest areas of interest from OEMs is how AI technology can identify visual or acoustic patterns related to quality defects. Can an image be used to identify a scratch on a cell phone casing or car paint job? Can acoustic sensors “hear” a poorly functioning dishwasher before the product is released from testing? The answers are yes and yes. IBM has two solutions – Visual Insights and Acoustic Insights – that use sophisticated AI to spot defects. What is even more impressive? These solutions can start with a small number of defective images or sounds and can learn over time to get smarter.

Does this mean we don’t need quality inspectors?

It is easy to position many of these AI-based solutions as replacing the jobs of quality inspectors. Yet this is rarely the case. Smart companies see these solutions as tools that help quality inspectors improve throughput and effectiveness. Put simply, technology like Visual Insights or Acoustic Insights help inspectors inspect products more quickly, with fewer misses, and fewer false positives. Rather than replacing inspectors, these technologies become important aids that help OEM respond better to the rising cost of quality without sacrificing margins.

Take the next step

Want to learn more about how IBM views quality and how we can help OEMs address quality challenges?

]]>https://www.ibm.com/blogs/internet-of-things/iot-industry-4-0-smart-manufacturers/feed/0Connected product engineering: what’s really needed for IoT product development?https://www.ibm.com/blogs/internet-of-things/connected-product-engineering/
https://www.ibm.com/blogs/internet-of-things/connected-product-engineering/#respondTue, 30 Jan 2018 09:00:26 +0000https://www.ibm.com/blogs/internet-of-things/?p=41243We are bombarded by news about the IoT and how it will change our lives—and, how product makers will need to change to keep up. But what does that really mean for product design and engineering processes? More connectivity means more complexity in the form of increased dependencies (or interdependencies) in product designs, which leads […]

]]>We are bombarded by news about the IoT and how it will change our lives—and, how product makers will need to change to keep up. But what does that really mean for product design and engineering processes?

More connectivity means more complexity in the form of increased dependencies (or interdependencies) in product designs, which leads to a greater need for requirements management and change management.

A big challenge facing companies moving into the IoT space is simply how to deal with all this new complexity. Systems engineering is a proven way of tackling the potentially overwhelming complexity of developing highly interconnected systems. Systems engineering has been around in industries such as aerospace and defence since the Apollo program in the ‘60s. Now it needs to be adapted and implemented in many new industries participating in IoT product development. For further thoughts on this topic see the recent article, Systems Engineering and IoT.

Product engineering

Designing and engineering connected products involves a greater number and variety of people in the organization, creating a need for more collaborative tools, and the ability to easily share information geographically, organizationally and between tools. In turn this means:

Web and cloud based tooling – available anywhere, with the security to ensure that only the authorised eyes have access.

Collaborative processes – where roles, workflows and deliverables are clear to everyone—so everyone knows what’s required and what’s needed to achieve the requirements in real-time. Again, web/cloud-based tooling allows all stakeholders to interact with project information at any time, regardless of geographical or organizational barriers.

Tools that can share information – so disciplines such as requirements management, architecture and design modelling, and quality management, which are very interdependent activities, can share information as openly as possible. Open technology initiatives such as Open Services for Lifecycle Collaboration are key to making this a reality. To ensure that product engineering is an optimally holistic activity, this sharing needs to link domains such as systems engineering, embedded and application development, and product lifecycle management.

Lastly, the IoT context fundamentally changes the dynamics of product engineering. For the first time, operational and usage data and analytics from connected products are now available to the engineering process. This feedback loop provides visibility into product performance and usage patterns, so engineers can validate design assumptions, and gain insights to factor into the product roadmap. Meanwhile, customer expectations are becoming dramatically heightened. It’s natural to think, “My smartphone apps are updated every day to fix bugs and to do new things—why not my IoT products?” These changes are driving a paradigm shift from research, then design, then make to continuous product improvement. Importantly, this shift must balance discipline in engineering practices to ensure confidence in the outcomes with the required pace of development to deliver competitive products with optimal speed to market. To accomplish this, organizations need:

An IoT feedback loop built into your business to provide uninterrupted information flows throughout the product lifecycle, not just between development engineering tools. This includes: (i) the ability to flow product operational information to analytical tools, and from analytical tools back into development processes, and (ii) the ability to flow software updates into the field at any scale of product deployment.

Agile engineering methods (for systems engineering and hardware development as well as software) – the ability to respond rapidly to new information and changing requirements and to continuously reprioritize engineering and development tasks to optimize the use of engineering resources.

Dependable engineering automation everywhere – from capturing traceability between all engineering artefacts, to automated testing, automated transformation of engineering information such as code generation, and finally automated documentation to help with compliance.

This blog is just a whistle-stop tour of some of the key areas in which product engineering is evolving to meet new challenges. Each point could be the starting point for a more in-depth article. But I’ll leave that for later posts. In the meantime, take a look at these resources:

]]>https://www.ibm.com/blogs/internet-of-things/connected-product-engineering/feed/0IoT weekly round-up: Thursday 25th January 2018https://www.ibm.com/blogs/internet-of-things/iot-weekly-roundup-25-january-2018/
https://www.ibm.com/blogs/internet-of-things/iot-weekly-roundup-25-january-2018/#respondFri, 26 Jan 2018 17:51:11 +0000https://www.ibm.com/blogs/internet-of-things/?p=63498This week, we’re delighted that IBM’s CEO Ginni Rometty is one of the chairs of the World Economic Forum in Davos, Switzerland. Elsewhere, Facebook and Element AI announce new artificial intelligence endeavours, and GM turns its attentions to autonomous driving tech. Davos forum chaired entirely by women This is a big one – the World […]

]]>This week, we’re delighted that IBM’s CEO Ginni Rometty is one of the chairs of the World Economic Forum in Davos, Switzerland. Elsewhere, Facebook and Element AI announce new artificial intelligence endeavours, and GM turns its attentions to autonomous driving tech.

Davos forum chaired entirely by women

This is a big one – the World Economics Forum in Davos, Switzerland will be chaired entirely by women. That’s a first in its 48-year history. We’re absolutely delighted that IBM CEO Ginni Rometty is one of them. Her co-chair is Norwegian Prime Minister Erna Solberg. Join the conversation on Twitter with the tag #WEF18.

Facebook welcomes new head of AI research

Facebook has hired a new executive to lead its AI research (FAIR) team. Jérôme Pesenti (formerly chief scientist for big data at IBM, so he must be good) will be leading the division’s 130 employees. The plan is to scale up rapidly, doubling the size of its research team in Paris to 100 people by 2022.

Element AI opens London outpost to support its ‘AI for good’ mission

More on AI, as Canadian startup Element AI announces plans to open an outpost in London. Last year, the group raised $102 million to launch new artificial intelligence services and systems. One of the new outpost’s focal projects will be ‘AI for good’ – working with charities and NGOs on AI tools to help everyone. Element AI also develops services for finance, manufacturing, robotics and logistics. The initial plan is to recruit around 20 engineers and developers for the London office.

GM launches tech center in Canada for autonomous driving

Automaker GM has opened a new dedicated tech facility in Canada. The Canadian Technical Centre (CTC) will support its work on autonomous vehicles, infotainment and advanced driver assistance features. It will house some 1,000 employees, 700 of whom will be dedicated engineers. The team will be working on technologies that support safe driving (in both cars with drivers and autonomous vehicles), such as lane-keeping.

Apple have announced a new Health Records section in their Health app, letting you view your medical records on your iPhone. The new feature forms part of iOS 11.3 and is currently in beta testing. Some hospitals and clinics are already partnering with Apple on this new initiative. The idea is to let patients add any CDA (Clinical Document Architecture) file to the Health Data section of the Health app. Johns Hopkins Medicine and Penn Medicine are already testing Health Records with their patients.